A spread spectrum system is a wideband system in which the entire frequency bandwidth of the system is available to each user all the time. The system expands or spreads the bandwidth of the transmitted information much more than the minimum bandwidth required to transmit the baseband data. The spreading of the data is performed using a spreading sequence, sometimes called a spreading code. Each user in the frequency bandwidth is distinguished from other users by the allocation of different spreading codes to each. Code Division Multiple Access (CDMA) systems are one kind of spread spectrum system.
Just as a CDMA transmitter spreads a signal across a bandwidth, a CDMA receiver compresses or de-spreads the received signal bandwidth in order to recover the original information. Since different users employ different spreading codes their respective transmissions can be separately decoded at a receiving station.
Spread spectrum systems have a number of advantages. First, CDMA receivers can diversity combine separate multi-paths using a RAKE receiver. A RAKE receiver enhances the capture of the received signal energy by allocating one of a number of parallel demodulators (referred to as “fingers”) to each of the strongest components of the received multipath signal. The outputs of all the RAKE fingers are combined (taking the best from each finger) after a corresponding delay compensation to construct an optimum received signal.
Second, CDMA systems tolerate interference up to a certain threshold limit. The introduction of additional active mobile radio transmissions to the CDMA system increases the overall level of interference at the cell site receivers (base stations) receiving CDMA signals from the mobile radio transmitters. Since all users employ the same frequency bandwidth, it is important that no one user dominates the bandwidth with high relative power transmission. The particular level of interference introduced by each mobile's transmission depends on its received power level at the cell site, its timing synchronization relative to other sites at the cell site, and its specific cross-correlation with other transmitted CDMA signals. For that reason, power control is very important in CDMA systems. Typically, power control attempts to achieve a constant mean power level for each mobile user received at a base station taking into account the transmission power at the mobile and the pathloss from the mobile to the base station.
The CDMA base stations control mobile transmit power of each mobile user based on Signal-to-Interference Ratio (SIR) measurements of mobile transmission received at the base station. The SIR is defined as the ratio of the data bit energy (Eb) to the interference (including noise) power spectral density (Io).
SIR measurements are compared with a reference Eb/Io, value, and depending on the result, the mobile is ordered to increase or decrease its transmit power by some predetermined amount, (e.g., 1 dB). Other kinds of SIR measurements can be used to adjust the reference Eb/Io level in order to achieve a specified frame error rate at the base station.
Thus, to ensure that no mobile station dominates the bandwidth by using excessive power levels, the system measures or determines Eb and Io values for each mobile. Based on those measurements, the system instructs the mobiles to adjust their power levels to appropriate, non-dominating values.
An estimation of data bit energy Eb can be performed after de-spreading and RAKE combining in the receiver. Depending on the SIR measurement application, it may be performed using a short or a long averaging period. A short averaging period is used when the Eb value is measured using only pilot preamble symbols transmitted at the beginning of each time slot within a data frame. For long-term SIR measurements, Eb values obtained for the pilot preamble and for each individual data symbol are averaged over the time slot period, and Eb values obtained from all slots are averaged at the end of the frame to produce the final long term Eb measurement value.
In both short and long term SIR measurement, the interference power Io may be averaged over a number of frames. More specifically, Io may be obtained by correlating the input signal multiple times with an uncorrelated (in the ideal case, orthogonal) spreading code or with time-shifted versions of the original spreading code used at the transmitter and averaging the multiple, squared, absolute correlation values over the number of frames.
The accuracy of the received signal level, interference level and received signal energy measurements and estimations are very important in the CDMA system to ensure good signal quality and maximum system capacity. Commonly-assigned U.S. Pat. No. 6,229,842, “Adaptive Path Selection Threshold Setting for DS-CDMA Receivers,” by Schulist et al is a prior method of interference level measurements. It, however, exhibits larger errors as increases, as shown in the graph of FIG. 1. As shown in FIG. 1, as increases, measurement error of the received interference level is dramatic. It is likely caused mainly by non-zero auto-correlation of the spread sequence, namely pn (K)·pn (K+t)10 when t10 where pn (K) is the spreading code for sample index K and pn (K+t) is the spreading code for an incremented (non-zero) sample index. The mean error shown in FIG. 1 depends on the received signal level and increases as increases.
An Ericsson-internal document “Base Station Demodulator,” by Ning He, illustrates and describes the specific structure of a demodulator that may form the basis for SIR measurement, estimation and correction in the present CDMA system. “Base Station Demodulator” also describes, beginning for example at page 23 and continuing, power and interference estimations and corrections. The measurement of received signal level provided by the methods described in that publication saturates at low values, as shown in FIG. 2. FIG. 2 illustrates that the relation between actual and estimated SIR is approximately linear for input values above about 10 dB; however, below 10 dB, the SIR measurement values saturate.
Saturation of SIR values is problematic in that the measured SIR value will be used by the base station to instruct the mobile to adjust its transmission power levels. Where the measurements linearly track the ideal SIR, the instructions from the base station will accurately reflect proper adjustments for the true input signal strength. But, at levels where the curve is saturated, the base station may provide power level adjustment instructions that bear little relation to the true input signal levels. At worst, the saturation can cause an unstable power control loop for certain input signal levels.
In the case of FIG. 2, the measurement error of the received signal level is caused mainly by the noise/interference component in the measurement. The mean error depends on the interference level and increases as Eb/Io decreases.
A combination of the signal measurements (FIG. 1 and interference measurements (FIG. 2) yields an SIR with saturation problems at both the upper and lower input values, as shown in FIG. 3. There, linearization between actual and measured SIR values is poor across most of the curve, but especially so below about 5 dB and above about 20 dB.
U.S. patent application Ser. No. 09/038,067 (filed Mar. 11, 1998), describes a piece-wise linearization method for correcting SIR measurements. Its method is quite sensitive in the saturation regions. In an example embodiment of that disclosure, an SIR correction function includes a linear part and a non-linear part, with the non-linear part corresponding to an inverse of an exponential function that approximates a non-linear portion of a curve corresponding to measured SIR values. In a second example embodiment, the linear part of the SIR correction function further includes first and second linear components to improve the accuracy of the correction function in certain situations. The parameters in the correction function in both of the first and second example embodiments are selected to minimize error between corrected SIR values and corresponding actual or ideal SIR values.
The present invention provides an alternative method of correcting SIR values in which the signal strength value and interference value are corrected separately. Since the errors associated with signal strength measurements and those associated with interference estimates derive from different sources, independent correction is found to provide improved overall SIR correction. Thus, unlike “Base Station Demodulation” where SIR per se is corrected (see for example equation 34 therein) and “Correction of signal-to-interference ratio measurements” by Popovic, where SIR per se is also corrected (see for example equations 3 and 4 and associated text), the present invention corrects the SIR by first correcting signal and interference values independently and then combining the corrected signal and corrected interference into a corrected SIR.